6 papers
Improved 3D Scene Stylization via Text-Guided Generative Image Editing with Region-Based Control
Haruo Fujiwara, Yusuke Mukuta, Tatsuya Harada
Recent advances in text-driven 3D scene editing and stylization, which leverage the powerful capabilities of 2D generative models, have demonstrated promising outcomes. However, ch…
Cross-Embodiment Offline Reinforcement Learning for Heterogeneous Robot Datasets
Haruki Abe, Takayuki Osa, Yusuke Mukuta +1
Scalable robot policy pre-training has been hindered by the high cost of collecting high-quality demonstrations for each platform. In this study, we address this issue by uniting o…
DEJIMA: A Novel Large-scale Japanese Dataset for Image Captioning and Visual Question Answering
Toshiki Katsube, Taiga Fukuhara, Kenichiro Ando +3
This work addresses the scarcity of high-quality, large-scale resources for Japanese Vision-and-Language (V&L) modeling. We present a scalable and reproducible pipeline that integr…
Gradual Transition from Bellman Optimality Operator to Bellman Operator in Online Reinforcement Learning
Motoki Omura, Kazuki Ota, Takayuki Osa +2
For continuous action spaces, actor-critic methods are widely used in online reinforcement learning (RL). However, unlike RL algorithms for discrete actions, which generally model…
Offline Reinforcement Learning with Wasserstein Regularization via Optimal Transport Maps
Motoki Omura, Yusuke Mukuta, Kazuki Ota +2
Offline reinforcement learning (RL) aims to learn an optimal policy from a static dataset, making it particularly valuable in scenarios where data collection is costly, such as rob…
HyperVQ: MLR-based Vector Quantization in Hyperbolic Space
Nabarun Goswami, Yusuke Mukuta, Tatsuya Harada
The success of models operating on tokenized data has heightened the need for effective tokenization methods, particularly in vision and auditory tasks where inputs are naturally c…